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Mostrando ítems 11-13 de 13
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Novel and Diverse Recommendations by Leveraging Linear Models with User and Item Embeddings
(Springer, 2020-04-08)[Abstract] Nowadays, item recommendation is an increasing concern for many companies. Users tend to be more reactive than proactive for solving information needs. Recommendation accuracy became the most studied aspect of ... -
Priors for Diversity and Novelty on Neural Recommender Systems
(M D P I AG, 2019-07-31)[Abstract] PRIN is a neural based recommendation method that allows the incorporation of item prior information into the recommendation process. In this work we study how the system behaves in terms of novelty and diversity ... -
Using Discrete Wavelet Transform to Model Whistle Contours for Dolphin Species Classification
(M D P I AG, 2018-09-17)[Abstract] This work proposes the use of features based on the discrete wavelet transform (DWT) for dolphin species classification. These features are compared with other previously used in the literature, and the experiments ...